Find the data first,then talk analytics
Most data programmes stall in the same place: nobody can say where a number came from, who depends on it, or whether it can be trusted. We begin with inventory and classification, then put the warehouse, lineage, quality and metrics onto a platform that runs.
Inventory first, tooling second
Inventory and classification first: systems, tables, interfaces and owners. The platform decision comes after. Projects that buy the tool first and look for the use case later tend to end at handover.
One platform for the warehouse and the governance
Modelling, lineage capture, quality rules and metric definitions are maintained together. A changed definition can be traced to everything downstream, so the dashboard and the model stop disagreeing.
Governance that feeds compliance
Classification results wire straight into access policy, masking rules and audit logs, so personal and critical data handling leaves an evidence trail regulators accept.
Data governance capability domains
Six domains from strategy through to steady-state operations — delivered on their own, or combined into a programme covering your core data domains.
Frequently asked questions
Common questions on scope, effort and self-hosted deployment. If yours is not here, talk to the data team directly.
It depends on the nature of the problem. If metric definitions conflict, downstream teams cannot use data without asking, and troubleshooting relies on individuals, what is missing is a catalogue, lineage and quality controls; another warehouse will not fix that. We begin with an assessment and keep what can be reused.
Customer story
Reallysec Empowers Siemens Digital Industries, Leading the Intelligent Future
With visualisation and analytics in place, Siemens DI gained full-path visibility into product master data flows, plus anomaly self-healing.